housing production subsidies and neighborhood revitalization_ new york city’s ten-year capital...

8/4/2019 Housing Production Subsidies and Neighborhood Revitalization_ New York Citys Ten-Year Capital Plan for Housing

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FRBNY Economic Policy Review / June 2003 71

Housing Production Subsidiesand NeighborhoodRevitalization:New York Citys Ten-Year

Capital Plan for Housing

perennial question in housing policy concerns the formthat housing assistance should take. Although some argue

that housing assistance should be thought of as a form of income support and advocate direct cash grants to needy

households, others favor earmarked assistancebut they differover whether subsidies should be given to the recipients asvouchers or to developers as production subsidies.

The appropriate composition of housing assistance hasrecently taken on particular import. In 2000, Congress createdthe Millennial Housing Commission and gave it the task of evaluating the effectiveness and efficiency of methods topromote housing through the private sector. As part of itsmandate, the commission is examining changes to existingprograms as well as the creation of new production programsto increase affordable housing.

This paper reexamines the debate over the appropriate formof housing assistance. First, we briefly summarize and evaluate

arguments in favor of demand-oriented housing subsidies(such as Section 8 vouchers) and supply-oriented housingsubsidies (such as production subsidies). We conclude thatalthough demand-oriented subsidies are preferable to supply-oriented subsidies on a number of grounds, governmentsupport for production may, at least theoretically, be justified

as a way to promote positive spillover effects and neighbor-hood revitalization. Whether sufficient spillovers exist is, in theend, an empirical question. Although much of the existingresearch finds little evidence of spillover effects, our findings onthe New York City experience suggest that spillovers may besignificant and large enough to justify government support forproduction.

Next, we describe the most extensive experiment in theUnited States in which a city used supply-oriented subsidies torebuild neighborhoodsNew York Citys Ten-Year CapitalPlan for Housing (the Ten-Year Plan). Born out of thenecessity to rebuild communities devastated by years of abandonment and arson, the program, launched by New York

Ingrid Gould Ellen is an assistant professor of public policy and urban planningat New York University; Michael H. Schill is a professor of law and urbanplanning at New York University and director of the universitys Furman Centerfor Real Estate and Urban Policy; Amy Ellen Schwartz is an associate professorof public policy at New York University; Ioan Voicu is the Furman Fellow atNew York Universitys Furman Center for Real Estate and Urban Policy.

The authors thank the Fannie Mae Foundation, the Lincoln Institute for LandPolicy, and the Furman Center for Real Estate and Urban Policy for fundingthis research. They also express gratitude to Jerilyn Perine, Richard Roberts,Harold Shultz, Calvin Parker, Ilene Popkin, and Harry Denny of the New YorkCity Department of Housing Preservation and Development for providing thedata necessary to complete this research. Finally, thanks are due FeliceMichetti for comments on a previous draft. The views expressed are those of the authors and do not necessarily reflect the position of the Federal ReserveBank of New York or the Federal Reserve System.

Ingrid Gould Ellen, Michael H. Schill, Amy Ellen Schwartz, and Ioan Voicu

A1. Introduction


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72 Housing Production Subsidies and Neighborhood Revitalization

City in 1986, ultimately led to the investment of more than$5.1 billion in housing in many of the citys poorestneighborhoods.

Finally, we describe the results of several empirical studieswe have recently completed on the effect of the Ten-Year Planon property values in New York City. Our results suggest thatthe use of production subsidies can indeed generate positivespillovers and contribute to neighborhood revitalization.Furthermore, by comparing and contrasting New York Citysexperiences with those of other cities, we explain why NewYork was so successful, and identify aspects of its program thatcould be transplanted to other cities.

2. Justifications for HousingAssistance: Revisiting theSupply-versus-Demand Debate

Although housing subsidies have become commonplace in theUnited States, it is still worthwhile to consider whetherhousehold financial assistance might be tied to housing ratherthan just provided as unrestricted cash grants. If the only housing-related problem facing Americans was insufficientincome among poor families to purchase adequate housing,then a strong argument could be made that unrestricted cashgrants would be best. In a liberal society dedicated to freechoice, allowing individuals to make their own decisions withrespect to consumption would generally seem desirable.Furthermore, considerable evidence suggests that unrestrictedcash grants would lead to increases in housing consumptionthat fall short of the grant amount (Polinsky and Ellwood1979). The implication is that earmarking subsidies for housingwould be a less efficient way than cash grants to enhancehousehold welfare. Finally, earmarked housing assistancecarries an additional inefficiencythe cost of administrationnecessitated by the requirement that the money be spent on aspecific good.

Despite the inefficiency, since the end of World War II,federal, state, and city governments have repeatedly tiedsubsidies to housing consumption. A number of justificationsmight be offered for this. First, consumers may have

incomplete information about the benefits and importance of adequate housing, leading them to spend too little on it. Peoplewho choose other goods and services before a minimum levelof shelter may do so because they lack sufficient information orare unable to assess rationally the true worth of decent housing,thereby justifying societal paternalism. Second, efforts to

provide a minimum level of housing consumption may benecessary to protect children from irresponsible parents, whowould, without government intervention, provide inadequatehousing for their children. Third, taxpayers may derive utility merely from the knowledge that people are not living indesperately deteriorated and unhealthy accommodations(Aaron 1972; Schill 1990; Olsen 2001). Thus, taxpayers may prefer that their tax dollars subsidize someones shelterdirectly, since it yields a greater increase in housingconsumption per public dollar spent than do cash transfers,even if housing subsidies are less useful to the recipient thancash transfers.

In addition to achieving redistributive and/or paternalisticgoals, earmarked housing assistance may be preferable to cashtransfers in addressing other economic and social objectives.Such goals might include lessening adjustment lags in supply and demand, ameliorating the impact of discrimination in thehousing market, improving the locations in which familieslive, and promoting positive spillovers and neighborhoodredevelopment (see Ellen, Schill, Schwartz, and Voicu [2001]).

The observation that earmarked housing assistance may further some or all of these objectives does not, however,suggest what form this assistance should take. In the remainderof this section, we examine what we have learned about therelative merits of different approaches. In particular, we discussthe advantages and disadvantages of supply- and demand-oriented housing subsidy programs.

According to recent estimates, the federal governmentprovides housing assistance to roughly 5.2 million renterhouseholds. An additional 9 million households qualify forassistance but do not receive it because housing subsidies areneither an entitlement nor a fully funded social welfareprogram (U.S. General Accounting Office 2001). This scarcity of subsidies makes efficient deployment of governmentresources crucial. Thus, it is important to begin by noting thatvirtually every empirical study performed over the past twenty-five years has found that demand-oriented subsidies (that is,vouchers and certificates) are more cost-effective than supply-oriented programs that subsidize the production of housing(including the public housing program, the Section 8 newconstruction program, and the low-income housing taxcredit). 1

A 2001 study by the U.S. General Accounting Office (GAO),

for example, compared the cost, both in total and in theamount borne by the federal government, of housing vouchersover a thirty-year period with the cost of housing built usingthe low-income housing tax credit, the HOPE VI program,Section 202, Section 811, and Section 515. According to theanalysis, the total per-unit costs for housing production


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programs ranged from 12 percent to 27 percent more than thecost of voucher programs (U.S. General Accounting Office2001, p. 2). In terms of the cost to the federal government, theproduction programs were between 15 percent and 38 percentmore expensive. 2

In addition to being cheaper than production programs,housing vouchers have typically led to better locational(neighborhood) outcomes. Supply-oriented programs operatewith a built-in contradiction: programs that try to target scarceresources to the neediest recipients (such as the public housingprogram) end up creating intensely concentrated poverty. Andthere is growing and persuasive evidence that concentrations of poverty are related to a wide variety of social problems,including high crime, dropout, welfare receipt, and teenagepregnancy rates. 3 Programs with less effective targeting (suchas HOPE VI or the low-income housing tax credit) foster moreeconomically integrated environmentsbut the cost is verticalinequity.

Housing vouchers resolve this contradiction. Because thevoucher recipient can rent housing in the private market(restricted only by maximum fair market rents), the morenarrowly a voucher program is targeted to the poor, the morelikely it is that deconcentration will occur. Indeed, research hastypically shown that the neighborhood outcomes of voucherrecipients dominate those who live in housing supported by production subsidies; voucher recipients see greaterimprovement in their neighborhood conditions than do publichousing recipients. As an example, using data from the 1990census, Newman and Schnare (1997) conclude that project-based assistance programs do little to improve the quality of recipients neighborhoods (and, in the case of public housing,

appear to make things significantly worse), while certificateand voucher programs reduce the probability that a family willlive in the most economically and socially distressed areas(pp. 726-7). They provide a powerful argument in favor of vouchers.

In some housing markets, however, vouchers may not liveup to their promise. In markets with extremely low vacancy rates, such as New York City in the late 1990s, voucherrecipients might experience significant difficulties identifyingstandard-quality housing with rents below federally prescribedmaximum levels. 4 Although this imbalance of supply anddemand might be a short-term phenomenon caused by a

sudden exogenous increase in demand for housing, it might bechronic and attributable to barriers (including regulatory barriers) in the housing market (Salama, Schill, and Stark1999).

In such tight housing markets, production subsidies can, inprinciple, enable households to obtain housing faster and more

cheaply than vouchers can. In practice, however, government-supported development is frequently slowed by bureaucraticdelays, neighborhood opposition, and political pressure.Moreover, if regulatory barriers are the problem, directgovernment provision is hardly the ideal responseinstead, amuch better solution would be to remove the barriers thatinterfere with the smooth operation of the housing market.

Subsidizing production can also, again in principle, be justified as a method of eliminating or ameliorating the effectsof discrimination in the housing market. 5 Discriminatory treatment may increase search costs, drive up the cost of housing for its victims, and interfere with optimal residentiallocation decisions. Since government provision should benondiscriminatory, direct provision of housing by governmentmay be proposed as a partial solution to the problem of housing discrimination. Unfortunately, some of the mostblatant acts of discrimination by landlords in the United Stateshave been committed by government agencies and some of themost segregated housing developments in the nation areowned by public housing authorities (Hirsch 1983).Furthermore, even if government could be relied upon tooperate in a nondiscriminatory manner, it is unclear whetherproduction programs would be the most effective way toameliorate the effects of housing discrimination. Instead, morevigorous enforcement of antidiscrimination laws may be moreeffective and preferable.

Although production programs do not have a comparativeadvantage over vouchers in cost-effectiveness or improvinglocational outcomes, and the case for relying upon them to dealwith market failures such as adjustment lags and discrimi-nation seems weak, production programs may be justified

by their ability to promote neighborhood development.Production programs may generate positive external benefitsto the neighborhoods in which they are located above andbeyond the benefits received by the housing consumersthemselves.

Because housing is fixed in space, its condition influencesthe value of neighboring properties. A dilapidated structure,for instance, can reduce the value of neighboring homes andmay lead to disinvestment in the neighborhood. Introducing ahigh-quality building might, however, generate positivespillovers and increase values and confidence in the area.Adding new housing might also bring new people to a

neighborhood, which may, in turn, improve neighborhoodsafety and fuel demand for retail services. If building owners donot bear all of the costs (or benefits) generated by theirproperties, the private sector will underinvest in housing.Public intervention, such as slum clearance or rehabilitationassistance, may therefore be appropriate.


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Similarly, production programs may generate infor-mational externalities. Housing developers may be averse toinvesting in distressed urban neighborhoods because they havelittle information about the demand for new housing in thearea. Housing investment in distressed neighborhoods, then,may be delayed or be insufficient because each developerhesitates to make the first move. Government, throughsubsidies and planning, can, in principle, encourage developersto make the first move, provide information, and thereby reduce risk (Caplin and Leahy 1998).

If any form of housing subsidy is likely to be capable of generating positive spillovers and catalyzing neighborhooddevelopment, it would seem to be production subsidies ratherthan vouchers. Indeed, the key shortcoming of productionsubsidiestheir concentration in spatially defined areasbecomes an advantage when it comes to neighborhoodrevitalization. Although vouchers increase demand and may well stimulate a supply response (including both new units and/or housing rehabilitation to meet minimum standards), their

reliance upon individual decisionmaking limits theireffectiveness in achieving spatially targeted goals. Individualvoucher recipients choosing where to rent housing do not takeinto account the effect their choice will have on the surroundingneighborhood and thus are unlikely to choose the locationswhere external benefits are maximized. Housing agencies andcommunity-based nonprofit organizations responsible forlocating and implementing production programs, however, aremore likely to consider the interests and needs of entirecommunities rather than just individual tenants.

It is unclear whether or not public officials and nonprofitdevelopers do, in fact, successfully deploy production subsidies

to create housing that generates positive spillover effects. As theremainder of this paper demonstrates, until recently, there hasbeen little evidence that government housing programsgenerate positive spillover effects and successfully promoteneighborhood revitalization. Nevertheless, our analysis of New York Citys Ten-Year Capital Plan for Housing,specifically designed to revitalize neighborhoods devastated by years of abandonment, has yielded strong evidence that thesespillover effects may be significant.

3. New York Citys Ten-YearCapital Plan for Housing

The results of our research on the spillover effects of affordablehousing investment differ substantially from those of earlierstudies. To some extent, these differences derive from the

particular circumstances and features of the programscomposing the Ten-Year Plan. Thus, this section describesthese programs, paying particular attention to those featuresthat may have been especially important in driving spillovereffects.

Throughout the twentieth century, New York City has beenamong the leading innovators in housing policy. In 1935, NewYork was the first city in the United States to build publichousing. New Yorks Fair Housing Practices Act of 1957 wasthe first law to make illegal discrimination against racialminorities by private landlords. In addition, the Acts Mitchell-Lama Middle Income Housing Program became a model forCongress when it passed the first below-market interest rateprograms, in the 1960s.

Thus, New York City Mayor Ed Kochs announcement of the Ten-Year Plan in 1985 was not entirely unprecedented.Indeed, many of the programs that would be encompassed inthe plan were already in existence in 1985, albeit at substantially lower rates of activity. The rough contours of the plan were firstannounced in the Mayors State of the City Speech (Koch 1985,p. 8). The goal was to renovate or build 252,000 units and makea financial commitment of $5.1 billion (City of New York1988). To fund the program, Koch proposed using money from the World Trade Center to finance approximately $1 billion in bonds. Other revenues would come from the citysHousing Development Corporation and its capital budget.

Certainly, a principal objective of the Ten-Year Plan was tocreate additional housing opportunities for low- andmoderate-income families as well as the homeless. In addition,a focus on neighborhood revitalization was evident from thebeginning of the plan. According to the mayor, first, we intendto undertake a major effort to rebuild entire neighborhoods of perhaps 15 to 25 square blocks throughout the City . . . it isanticipated that such concentrated revitalization wouldprovide the hub for further development (Koch 1985, p. 11).A 1989 report by the New York City Department of HousingPreservation and Development (HPD) made the point evenmore explicitly: Were creating more than just apartmentswere re-creating neighborhoods. Were revitalizing parts of the city that over the past two decades had been decimated by disinvestment, abandonment, and arson.

In New York Citys Ten-Year Plan, the location of housinginvestments was, to some extent, dictated by where the city owned property. During the late 1970s, the city had takenownership of more than 100,000 vacant and occupied apartmentsas a result of tax foreclosure. This so-called in rem housing,named after the legal action that vested title in the city, wouldprovide the raw material for the lions share of the program.

Over time, HPD created a vast array of programs thatenlisted a wide variety of actors. Because neighborhood


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preservation and revitalization were important objectives of the plan, the city implemented programs that madecommunity-based nonprofit organizations the majorstakeholders in housing production. According to FeliceMichetti, a former HPD commissioner and one of the principalarchitects of the plan, when the Ten-Year Plan began, therewere about twelve not-for-profits in the City of New York thatwere actively involved in housing . . . . By the time I left HPD,there were over a hundred not-for-profits involved in the Ten-Year Plan, and involved not in the traditional federal role of sponsoring projects, but actively involved [in development](New York City Department of Housing Preservation andDevelopment 2000, p. 25). For-profit housing developers werealso active participants, attracted by the development fees orthe promise of long-term property value appreciation. Localfinancial institutions and intermediaries were activeparticipants as well.

Over the course of the Ten-Year Plan, the city utilized atleast 105 programs, many of which produced only a handful of

units. Although the majority of these programs involvedrenovation of occupied housing, our focus in this paper is onthe 66,147 new housing units createdthrough either newconstruction or the gut rehabilitation of formerly vacantbuildings. 6 In most instances, the citys subsidy for housing wasnot limited to capital dollars. Most newly constructed orrehabilitated housing also qualified for property taxabatements and/or exemptions. 7 We divide these programsinto four categories, based on whether they involved new

construction or gut rehabilitation and whether they were slatedfor homeownership or rental use. Table 1 shows the distri-bution of Ten-Year-Plan units across these four categories. Thebulk of the units were rental, created from the gut rehabilitationof formerly vacant buildings.

4. Evidence of Spillover Effects:New York City and Elsewhere

Here, we review the results of our recent empirical work onthe effect of the New York Citys Ten-Year Capital Plan forHousing on property values in the city. We compare andcontrast New York Citys experiences with those of other citiesto explain why New York was so successful as well as whichaspects of its program might be successfully transplanted toother cities.

4.1 Evidence from New York City

Using a unique administrative data set, we have completed aseries of studies on New York Citys Ten-Year Capital Plan forHousing (Ellen, Schill, Susin, and Schwartz 2001; Schill, Ellen,Schwartz, and Voicu 2001; Ellen, Schill, Schwartz, and Voicu2001). Although each of our studies has differed in focus, ourcore objective was to examine whether investments in place-based housing programs have an effect on the value of homesin surrounding neighborhoods and to derive estimates of thesign and significance (both substantive and statistical) of theseeffects. All three studies found evidence of positive andsignificant spillover effects.

Our first study explored the effects of the Nehemiah Planand the New Homes Program of the New York City Partnership, both of which subsidize the development of affordable, owner-occupied homes in distressed urbanneighborhoods (Ellen, Schill, Susin, and Schwartz 2001). In thesecond study, we expanded the analysis to consider the effectsof a wider range of housing subsidized through the Ten-YearPlan; for instance, we analyzed the effects of rental andhomeownership programs and renovation and rehabilitationas well as new construction programs (Schill, Ellen, Schwartz,and Voicu 2001). For the third study, we restricted our analysisto the effects of newly created units, investigated differences inspillover effects across types of housing programs, andprovided some evidence to suggest how the magnitude of thespillover benefits generated by these units compared with theirapproximate costs (Ellen, Schill, Schwartz, and Voicu 2001).

Table 1

Distribution of Ten-Year-Plan New Housing Unitsby Program Class

Units

Program Class NumberPercentage

of Total

Owner-oriented programsRehabilitation of vacant buildings 2,801 4.2New construction 16,813 25.4

Total owner-oriented programs 19,614 29.7

Renter-oriented programs

Rehabilitation of vacant buildings 41,484 62.7New construction 5,049 7.6Total renter-oriented programs 46,533 70.3

Total all classes 66,147 100.0

Note: Figures include all Ten-Year-Plan new housing projects in theNew York City Department of Housing Preservation and Developmentdatabase.


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For consistency with other analyses (which typically focuson new units) and for brevity, we mainly review the methodsand results of our most recent study of newly created units. Ourbasic empirical strategy in all of these studies, however, was thesame: we used a difference-in-difference model to compare thesales prices of properties within 500-foot rings of Ten-Year-Plan sites to the prices of comparable properties in the samecensus tracts (but outside the rings). We then compared themagnitude of this difference before and after the completion of a Ten-Year-Plan project to estimate the effect of the housinginvestment on property values.

More formally, we used a fixed-effects hedonic price model,adapted from Galster, Tatian, and Smith (1999), whichcontrols for structural characteristics of the property. In thismodel, the fixed effects are specified as census tract, quarter-specific fixed effects.8 In other words, we effectively included aseparate dummy variable for each census tract for each of theseventy-nine quarters in our data. 9 This allowed us to controlfor neighborhood-specific price changes over our time period.

The core equation we estimated is shown below, whereis the log of the sales price (per unit) of property i in

census tract c in quarter t ; is a vector of property-relatedcharacteristics, including age and structural characteristics(square footage, lot size, garage); and is a vector of locational attributesspecifically, a set of what we call ringvariables: whether a sale is within 500 feet of a Ten-Year-Plansite, whether any units are completed within this distance, and,if so, the number and mix of the completed units. Finally,

are a series of dummy variables indicating the quarter andcensus tract of the sale. 10

(1) .

To help explain our identification strategy, Table 2 providesa list of ring variables. First, we include a series of in-ringdummy variables, which indicate whether a property sold iswithin 500 feet of a particular type of Ten-Year-Plan project,whether completed or not. Because different kinds of projects

P ic t ln

X it

Z it

I ct

P ict ln X it Z it ct I ct it + + + +=

Table 2

Main Ring Variables

Variable Definition

In ring, new units, owner but not renter1-100 units 1 if the property sold is within 500 feet of 1-100 homeownership new units, whether completed or not,

but not of rental new units; 0 otherwise101+ units 1 if the property sold is within 500 feet of more than 100 homeownership new units, whether completed

or not, but not of rental new units; 0 otherwise

In ring, new units, renter but not owner1-100 units 1 if the property sold is within 500 feet of 1-100 rental new units, whether completed or not, but not

of homeownership new units; 0 otherwise101+ units 1 if the property sold is within 500 feet of more than 100 rental new units, whether completed or not,

but not of rental new units; 0 otherwise

In ring, new units, owner and renter1-100 units 1 if the property sold is within 500 feet of 1-100 homeownership and rental new units, whether

completed or not, but not of rental new units; 0 otherwise101+ units 1 if the property sold is within 500 feet of more than 100 homeownership and rental new units, whether

completed or not, but not of rental new units; 0 otherwise

Post ring, new units 1 if the property sold is within 500 feet of any completed new units; 0 otherwiseNumber of new units at time of sale Number of completed new units within 500 feet of the property sold(Number of new units at time of sale) 2 Squared number of new units at time of sale

Share of multifamily new units at time of sale Share of completed new units within 500 feet of the property sold that are in multifamily buildingsShare of rental new units at time of sale Share of completed new units within 500 feet of the property sold that are rentalsShare of new construction units at time of sale Share of completed new units within 500 feet of the property sold that are in newly constructed

buildingsTpost , new units Years since earliest completion of new units within 500 feet of the property sold; 0 if no new units were

completed before saleTpost *(number of new units at time of sale) Interaction term

Note: New units is defined as newly constructed units and rehabilitated (formerly) vacant units.


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Price relative to rest of tract

Chart 1

Percentage Price Differences in 500-Foot Ringand Surrounding Tracts, by Number of Units BuiltRings with Homeownership Units Only

Note: Price gaps are for before and after the completion of Ten-Year-Plan new units.

-10-8

-6

-4

-2

0

2

46

10 units 100 units 200 units

Price gap before completionPrice gap after completion

may have been located in different kinds of neighborhoods, wedefined six mutually exclusive in-ring variablespropertieswithin 500 feet of large homeownership projects, smallhomeownership projects, large rental projects, and so on.Second, we included a post-ring variable that indicates if thereare any completed units within 500 feet of the sale. Thecoefficient on this variable indicates the extent to which, afterthe completion of a development of any size, sales prices rise inthe vicinity relative to the average increase in the larger censustract. Third, we controlled for the number of completed unitswithin this distance and the share of completed units that werein multifamily structures, were rentals, and were in newly constructed buildings. Finally, we include Tpost , which indi-cates the years since completion, and Tpost interacted withnumber of completed units to see if the effect changed overtime and whether this change was shaped by the size of theproject.

To estimate this model, we used a combination of three geo-coded administrative data sets. First, we used detailed data onthe location (down to the block level) of all housing built orrenovated through the Ten-Year Plan. Second, through anarrangement with the New York City Department of Finance,we obtained a database that contains sales transaction prices forall apartment buildings, condominium apartments, and single-family homes over the 1980s and 1990s. 11 We used GIStechniques to measure the distance from each sale to all Ten-Year-Plan sites. Our final sample in the three studies rangesfrom 234,000 to 294,000 property sales, a very large sample sizecompared with much of the literature.

Third, we supplemented these transaction data withbuilding characteristics from an administrative data set

gathered for the purpose of assessing property taxes (the RPADfile). The RPAD data contain information about buildings butdo not contain much information about the characteristics of individual units in apartment buildings (except for condo-miniums). Nonetheless, these building characteristics explainvariations in prices surprisingly well (our final R 2s exceeded0.87), suggesting that the data are rich enough for estimatinghedonic price equations.

Our results consistently show that the completion of newhousing units under the Ten-Year Plan was associated withincreased sales prices of nearby properties. For example,Charts 1 and 2 show the regression-adjusted percentagedifference between prices in the ring and prices in the largercensus tract, before and after the completion of a project.Specifically, Chart 1 shows how prices in the ring changed aftercompletion of a Ten-Year-Plan homeownership project of three different sizes. The first set of bars shows that before thecompletion of a ten-unit homeownership project, the sales

price of a property located within 500 feet of a future site wason average 6.8 percent lower than the price of a comparableproperty sold in the same quarter in the same census tract.After completion, the gap shrunk so that prices in the ring wereonly 3.1 percent lower than prices in the larger census tract.

As can be seen from Chart 1, the impact appears to begreater for larger projects. The second set of bars shows that,before completion of a project with 100 homeownership units,the sales price of a property located within 500 feet of the futuresite was, on average, 6.8 percent lower than the price of acomparable property sold in the same quarter in the samecensus tract. 12 After completion, prices in the ring actually ended up higher than those in the surrounding census tract.Similarly, for properties within 500 feet of homeownershipsites with 200 units, the ring/census tract gap shifted from an8.4 percent shortfall in the ring to a 3.9 percent premiumafter completion.

For properties within 500 feet of renter-oriented Ten-Year-Plan projects, we obtained very similar results (Chart 2). Theone key difference is the very large price gap for propertieslocated within 500 feet of a site that will ultimately hold 200rental units. We estimated that before completion, prices of properties near such large rental project sites were a full17 percent lower on average than prices of comparableproperties located outside the ring, but in the same censustract. After completion, the gap decreased by more than12 percentage points.

There are several points to highlight here. First, in all cases,quality-controlled property values were lower for properties


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Price relative to rest of tract

Chart 2

Percentage Price Differences in 500-Foot Ringand Surrounding Tracts, by Number of Units BuiltRings with Rental Units Only

Note: Price gaps are for before and after the completion of Ten-Year-Plan new units.

-20

-15

-10

-5

0

5

10

10 units 100 units 200 units

Price gap before completion

Price gap after completion

located within 500 feet of Ten-Year-Plan sites than forcomparable properties located beyond this distance but in thesame census tract. Ten-Year-Plan housing, in other words, wastypically located in the most distressed micro-neighborhoodswithin a census tract. Furthermore, the larger the project, themore that distressed property values tended to be in thevicinity, and rental projects appear to have been sited in evenmore distressed neighborhoods than homeownership projects.These projects, in other words, were not randomly located,emphasizing the need to control for these baseline conditionswhen estimating effects.

In addition, the value of properties near Ten-Year-Plan sitestypically rose significantly relative to prices in their census tractafter completion of a project, and this increase was sustainedover time. (The coefficient on the post-completion time trendin the ring was statistically insignificant. 13) A final, notablepoint is that the greater the number of units, the greater theeffect. With this said, we found a relatively large, positivefixed effect common to projects of all sizes. One inter-pretation of this result is that much of the positive spillovereffect may derive from the elimination of existing blight; thescale or size of the project is less important than the fact that atleast some units were built.

Consistent with this interpretation, we found that the typeof project made little difference in determining effects. Wefound no statistically different effects between rental andownership projects, or between units created through therehabilitation of vacant buildings and those built throughnew construction. Structure type was also irrelevantthemagnitude of the spillover effect was unchanged whether the

project was made up of one-to-four-unit buildings ormultifamily apartment buildings.

In summary, we found that the units created through theTen-Year Plan generated significant and sustained positivespillover effects on neighboring properties, indeed, benefitsthat were quite large relative to city subsidies (Ellen, Schill,Schwartz, and Voicu 2001). We next review evidence fromother cities, then speculate as to whether our positive resultsmight be unique to New York City and the particular effortsmade under the Ten-Year Plan.

4.2 Evidence on the Effects of OtherSupply-Side Programs

Although several studies have attempted to quantify thespillover effects of place-based subsidized housing, few havefound statistically significant effects. Some studies have foundsmall, positive effects (De Salvo 1974; Rabiega, Lin, andRobinson 1984), yet the general conclusion has been that thedevelopment of subsidized housing has had little or no effecton surrounding neighborhoods (Nourse 1963; Schafer 1972;see Matulef [1988] and Goetz, Lam, and Heitlinger [1996] fora review of the literature). Indeed, attempts to quantify theeffect of housing quality more generally on the value of neighboring properties have largely yielded insignificantresults. As Mills and Hamilton (1994) write, researchers havealmost uniformly failed to find significant and consistenteffects of neighboring activities on property values. Althougheconomists have not rejected the possibility of spillover effects,

they speculate that such effects operate mainly in high-density neighborhoods, are probably highly localized, and only matterwhen housing is badly deteriorated or abandoned (Mills andHamilton 1994).

During the 1990s, three studies were published suggestingthat proximity to subsidized housing can affect neighboringproperty values, but the effects were typically negative, at leastin the case of federally subsidized rental developments (Lyonsand Loveridge 1993; Goetz, Lam, and Heitlinger 1996; Lee,Culhane, and Wachter 1999). Other recent studies havesuggested no significant effect (Briggs, Darden, and Aidala1999; Cummings, DiPasquale, and Kahn 2001).

One recent paper comes to a more hopeful conclusionabout place-based subsidies. Santiago, Galster, and Tatian(2001) used a hedonic model with localized fixed effects tostudy whether the purchase and renovation of property by theDenver Housing Authority, and its conversion into subsidizedhousing, influenced the subsequent sales prices of surrounding


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single-family homes. The authors found that proximity todispersed public housing units was, on average, associated witha modest increase in the prices of single-family homes. But they found that these positive benefits were weakest in the poorestareas. Indeed, the effects were consistently negative insubstantially black neighborhoods. This contrasts sharply withour research on New York City, which found substantialpositive effects in the citys poorest neighborhoods.

4.3 Why Are New York CitysResults Stronger?

We have several hypotheses for why our results suggest largerand more positive spillover effects: differences in data andmethods, more favorable housing market conditions, a morefavorable mix of housing, a greater level of municipalcommitment, and a greater focus on neighborhoodrevitalization. Note that another possible difference is timing

most prior research examined large-scale federal housingprograms from an earlier era. There may be commonmacroeconomic, sociological, or political explanations fordifferent outcomes in those earlier periods. Thus, whencomparing our results with those for other cities, we pay particular attention to six studies that have focused on morerecent housing programs: Lyons and Loveridge (1993), Goetz,Lam, and Heitlinger (1996), Lee, Culhane, and Wachter

(1999), Briggs, Darden, and Aidala (1999), Cummings,DiPasquale, and Kahn (2001), and Santiago, Galster, andTatian (2001). Table 3 provides summary information on thesestudies.

Data and Methods

It is possible that the differences in results are rooted indifferences in data and methods. Our study is based on anextraordinarily rich data set. The large number and variety of housing units built, the long time frame, and the large volumeof sales data allow us to employ a data-intensive methodology that incorporates many of the best features of previous studies.

The most important methodological challenge in estimatingthe effect of subsidized housing is identifying the appropriatecounterfactual. One approach is to compare price levels inareas receiving subsidized housing with comparable propertiesthat have no subsidized housing. This yields an unbiased

estimate of the effect if the only difference between the areas isthe housing investmentwhich is difficult to determine. If theprices of homes tend to be lower near subsidized housing sites,is this because the development of subsidized housingdepressed housing values or because the subsidized housingwas located in a more distressed area? A second approachcompares property values before and after housing investment,which yields an unbiased estimate of the effect if there is no

Table 3Projects and Units in the Analyses of Assisted Housing Effects

Author Housing Program City

Number of Subsidized

UnitsNumber of Projects/

Developments Study Period

Number of Home Sales/ResidentialProperties

Briggs et al. (1999) Dispersed Yonkers, New York 200 7 1985-96 3,101Santiago et al. (2001) Dispersed Denver 118 a 92 1987:1-1997:3 43,361Cummings et al. (2000) Homeownership Philadelphia 311 2 1986-97 146,053Lyons and Loveridge (1993) Multiple federally assisted Ramsey County,

Minneapolis12,864 120 1991

26,503b

Goetz et al. (1996) Nonprofit developed Minneapolis 476 23 1994 22,156Lee et al. (1999) Multiple federally assisted Philadelphia NA c 1989-91 18,062

aThis is an estimate based on average number of households per site reported in the authors Table 1, Selected Characteristics of 1989-1997 VintageDispersed Housing Sites (p. 75).

bThis is a 25 percent sample of the 128,010 nonsubsidized residential units in Ramsey County.

cThe authors do not report total number of units; however, they do include dummy variables for large and high-rise public housing developments.Large is not defined.


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other force shaping the growth in property values at the sametime as the housing investment. But again, there may be otherforces affecting the target neighborhood that coincide withdevelopment of subsidized housing, complicating the effort todisentangle the specific effect of subsidized housing. Finally,effects can be investigated by constructing and estimating aneconometric model that fully specifies the determinants of property values, including the neighborhood characteristicsand housing investments. Here, unbiased impact estimatescan only be obtained if the model includes all relevantneighborhood characteristicsa formidable challenge. (SeeGalster, Tatian, and Smith [1999] for a fuller discussion of alternative approaches to estimating impacts of subsidizedhousing.)

Using more detailed data and a clever methodology,Santiago, Galster, and Tatian (2001) are able to sort outcausality more persuasively than the other studies, andtherefore we place more weight on their results. They use ahedonic model with localized fixed effects and, in contrast to

earlier research, they also control for past trends in housingprices in the immediate vicinity of a project. That is, they control for both past levels and trends in housing prices in thebaseline neighborhood and therefore control for any tendency of the housing authority to develop housing in neighborhoodswhere prices were already rising.

We adapt their methodology in our approach, and ourresults are, in some sense, most comparable to theirs. As notedearlier, we estimate effects based upon the assumption that inthe absence of the Ten-Year-Plan units, properties within500 feet of the sites would have appreciated in value at the samerate as comparable properties in the same census tract, but

outside of the 500-foot ring. That seems particularly reasonablegiven the small size of these rings. Put differently, our estimatesare identified as the difference in the growth in property valuesbefore and after the housing investment relative to the growthin prices in a comparable areaoutside the ring but in thesame census tract. Thus, our methodology combines the best of the alternative strategies described above and, as a result, ourfindings are less likely to be biased. (Our estimates will bebiased only if there was some force affecting property valuesdifferentially inside and outside the ring at the same time as thehousing investment.)

Equally important, our analyses are based on a rich data setincluding information on an extraordinarily large number of transactions and an enormous number of units. As shown inTable 3, earlier studies typically examined the effect of severalhundred subsidized units, spread across a number of projects.By contrast, we examined the effect of approximately 66,000new subsidized units, developed at different times over several

years, in a wide range of neighborhoods. Thus, it is harder tobelieve that some other contemporaneous phenomenon wasresponsible for lifting property values in the proximity of theTen-Year-Plan units while leaving properties outside the ringbut in the same neighborhood unaffected. One would have tobelieve that this phenomenon occurred at different times indifferent neighborhoods at the same time as the housinginvestment.

Note that the small number of subsidized units examined inmany of the other earlier studies has made it difficult to formsharp estimates. Although estimated effects may have beenpositive, standard errors are large. Briggs, Darden, and Aidala(1999) and Cummings, DiPasquale, and Kahn (2001), forinstance, found that subsidized housing had a positive butstatistically insignificant effect on surrounding property values.It may be that a larger number of projects would have yieldedsmaller standard errors and found positive and statistically significant effects. (It is also possible, of course, that expandingthe number of projects would have revealed negative andsignificant effects.)

Housing Market Conditions

A second possible explanation for the difference in findings isthat housing market conditions were simply more propitiousin New York City than elsewhere. During this time, the city wasgaining population largely fueled by enormous waves of immigration, in sharp contrast to Philadelphia (where two of these earlier studies were undertaken), which lost 4 percent of its residents between 1990 and 2000. Vacancy rates were alsoquite low in New York City during this timethe rentalvacancy rate in the city fell to 3.2 percent in 1999 (Daniels andSchill 2001). Vacancy rates in the Philadelphia metropolitanarea were, by comparison, more than 8 percentandundoubtedly higher still in the city itself. As noted above, place-based housing programs are likely to be most effective in tighthousing markets, where they can help to meet growingdemand. Thus, the difference in findings may reflect whatcommon sense (and economics) suggests. In cities likePhiladelphia in the 1990s, with a shrinking population andhigh vacancy rates, housing investment is likely to have (atbest) little effect on values of neighboring propertiesaninfusion of new housing was probably not what the citysdistressed neighborhoods needed. Indeed, additional housingmay have promoted filtering and the removal of buildings fromthe housing stock. In growing New York City, with very littlevacant housing and a preponderance of structural barriers thatinhibit construction of affordable, private housing (Salama,


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Schill, and Stark 1999), public housing investment may havebeen a highly effective spur to neighborhood economicdevelopment.

Alternatively, New Yorks extraordinarily high density may also have contributed to the larger effects. Clearly, we wouldexpect spillover effects to be larger in neighborhoods withhigher densities. In 1990, population density was more thantwice as high in New York City than in Philadelphia and threeand a half times as high as it was in Minneapolisthe site of three of our comparison studies.

Mix of Housing

A third possible explanation for New Yorks difference con-cerns the type of housing built by the city. That is, the mix of housing built in New York may have been disproportionately composed of the type that would generate larger neighborhoodspillover effects. Although plausible, this explanation isundermined to some extent by the fact that our research foundno differences in spillover effects across different types of housing. In addition, New Yorks focus on income mixing may have made a difference. Rather than concentrating the very poorest households in particular neighborhoods or projects,the city generally aimed to create housing with a mix of incomes.

Level of Commitment

New York Citys Ten-Year Plan may have had a greater effectthan initiatives of other cities because of New Yorks level of commitment. Mayor Koch, in announcing the Ten-Year Plan,placed his prestige and that of his housing agency on the line incommitting the city to an effort of unprecedented magnitudeand scope. This commitment, together with the quality of thestaff assembled at the housing agency, may have generatedconfidence on the part of neighborhood residents, financialinstitutions, and investors, encouraging them to contributetheir own resources and time to revitalization activities.

Focus on Neighborhood Revitalization

Finally, the explanation may lie in New York Citys explicitemphasis on neighborhood revitalization. As noted above, oneof the key objectives of the Ten-Year Plan (if not the key objective) was to reclaim parts of the city that had beendestroyed by arson and disinvestment during the 1970s. In the

programs evaluated in other cities, this aim was far less central.In the scattered-site public housing initiatives, for instance, thegoal was to offer housing opportunities to poor families inlower poverty communities (Briggs, Darden, and Aidala 1999;Santiago, Galster, and Tatian 2001). Therefore, it is perhaps notsurprising that New York appears to have been more successfulin developing housing that benefited the surroundingcommunities. 14

Furthermore, New York City chose sites (either buildings orvacant land) that were extremely blighted, so that even modestimprovements may have been able to generate dramaticimprovements in the blocks surrounding them. Many of thecities examined by other researchers were unlikely to havefaced such pockets of abandonment. If they did, the studiesmay not have so explicitly targeted them. Indeed, in Denverand in Yonkers, New York, the aim was to select sites inmiddle-class neighborhoods. These were hardly areascharacterized by the same devastation as the neighborhoodsstudied in New York City.

4.4 Evidence on the Effects of Demand-Oriented Subsidies

Ideally, we would like to obtain estimates of the spillover effectsof tenant-based vouchers to compare with the housing builtunder the Ten-Year Plan. Unfortunately, such estimates areunavailable. Nevertheless, for the reasons discussed above (forexample, tenants are likely to be dispersed and the aim of voucher programs is typically not to revitalize neighborhoods),

it is unlikely that vouchers would deliver spillover effects of themagnitude we found generated by the Ten-Year Plan.This expectation is modestly supported by other research.

Galster, Tatian, and Santiago (1999), for example, examine theeffects of Section 8 tenants on neighboring properties in thesuburbs surrounding Baltimore. They find, in general, thatproximity to a small number of Section 8 tenants is linked topositive changes in property values. But closer inspectionshowed that these small positive effects were limited toproperties within 500 feet of no more than six voucher holders.For properties close to larger numbers, the net effect proved tobe negative, and these negative effects were quite substantial for

the largest concentrations of tenants (more than fifty tenants).Moreover, when looking across different types of neighbor-hoods, the authors find that the positive effects were in factlimited to high-value, largely white neighborhoods, as was thecase in their analysis of scattered-site public housing in Denver.

In short, the authors conclude that Section 8 demand-sidesubsidies can be used to generate neighborhood externalities,


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but only in higher valued, appreciating, largely whitecommunities. The irony, of course, is that these are hardly thesorts of neighborhoods where we are likely to be very concerned about improving neighborhood quality.

Two other studies examine the effect of voucher householdson property values: Lyons and Loveridge (1993) find no effecton surrounding property values and Lee, Culhane, andWachter (1999) uncover slight negative effects on surroundingproperty values. In short, prior research provides little supportfor the notion that vouchers are likely to lead to the same large,positive spillover effects on surrounding properties that weestimate were generated by the Ten-Year Plan.

5. Conclusion

Since the mid-1970s, the central debate among housing policy analysts and government officials has revolved around therelative advantages and disadvantages of housing vouchersversus supply-oriented subsidies. Study after study demonstrated the comparative advantage of vouchers on avariety of groundsranging from their lower cost to the betterneighborhoods they enable their recipients to live in. Economictheory has suggested that production programs might do betterthan housing vouchers in generating positive spillovers andneighborhood revitalization, but empirical studies have neverquite supported this theory.

New York Citys Ten-Year Capital Plan for Housing pro-vides advocates of production programs with more optimisticresults. Our findings suggest that New Yorks unprecedentedexpenditure of $5.1 billion on housing production programshas generated substantial positive spillovers and contributed toneighborhood revitalization. The rebuilding of extraordinarily depressed neighborhoods in the South Bronx, Central Harlem,and Central Brooklyn seems to have been achieved not just as aresult of a booming economy and a growing population, butalso because of an innovative and massive investment of publicdollars.

Although our research on the utility of productionprograms as a neighborhood revitalization tool in New Yorkprovides some evidence of the contributions that productionprograms can make in distressed neighborhoods, moreresearch is needed. First, our study did not directly compare thespillovers generated by production programs with those thatmight accompany housing vouchers. Second, whether thesuccess in New York City can be replicated elsewhere remainsvery much an open question. Third, production programs suchas those utilized by New York City are extremely costly. Ourresearch suggests that the benefits achieved in terms of increased property values may outweigh the costs of thesubsidies, yet much more work remains to be done before thatconclusion can be stated with any level of assurance.


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Endnotes


1. For an overview of the theoretical and empirical evidence on therelative cost-effectiveness of housing vouchers and certificates, seeSchill (1993). One recent article has made a counterargument(McClure 1998); Shroder and Reiger (2000) have challengedMcClures methodology.

2. According to the report, these estimates of the cost differentialbetween voucher and production programs were conservative. They did not include the value of tax abatements granted by localities fornew construction, nor did they include funding of capital reserves.The authors estimated that including these costs would have increasedthe differences between the two types of subsidy programs by about10 percent.

3. For a summary of the literature on the neighborhood effects of

concentrated poverty, see Ellen and Turner (1997).

4. A recent paper by Bahchieva and Hosier (2001) indicates thatbetween October 1999 and June 2000, 2,263 vouchers issued by theNew York City Housing Authority for nonemergency reasons werepicked up by applicants. Only 1,339 applicants successfully rented aunit with their vouchers; 1,124 failed to obtain a unit before expirationof their vouchers.

5. Recent evidence suggests that black and Latino homeseekersencounter unfavorable treatment approximately half of the time they transact in the housing market (Ondrich et al. 1999).

6. In this paper, units built or rehabilitated under the Ten-Year Planare defined to include only projects completed between January 1987and June 2000. The January 1987 beginning date was selected becauseof the long lag time associated with housing construction. It is likely that buildings completed in 1986 were planned and financed longbefore the announcement of the plan. In addition, when we countunits produced through the plan, we do not include housing unitsbuilt under federal programs such as public housing, Section 8, andSection 202 housing. In certain respects, our definition of the Ten-Year Plan is therefore both under- and overinclusive. Federal housingprograms that made use of city resources such as city-owned land

would not be included in our totals. In addition, it is possible thatcompletions after 1986 would be included even though planning may

have begun and funding commitments for the developments may have been made before the announcement of the plan in 1985.

7. For more details on financing, see Schill, Ellen, Schwartz, and Voicu(2001).

8. Note that Galster, Tatian, and Smith (1999) include census-tractfixed effects instead, which assumes neighborhood fixed effects areconstant over timean assumption that seems unrealistic over a timeperiod as long as ours.

9. Ellen, Schill, Susin, and Schwartz (2001) used ZIP code fixed effects.

10. In Ellen, Schill, Susin, and Schwartz (2001), we also estimate anumber of alternative specifications (for instance, providing year-by-

year estimates of post-completion effects), but all rely on the samefundamental difference-in-difference approach.

11. Because sales of cooperative apartments are not considered sales of real property, they are not recorded and were thus not included in ouranalyses. We should also note that most of the apartment buildings inour sample are rent-stabilized. Given that legally allowable rents aretypically above market rents outside of affluent neighborhoods inManhattan and Brooklyn, we do not think that their inclusion biasedour results (see Pollakowski [1997]).

12. Our specification allowed the precompletion price gap to differ

only for projects above and below 100 units.

13. In our first paper, we found that the impact of Partnership andNehemiah homes declined over time within the 500-foot ring. Effectson properties somewhat more distant from the subsidized homes werepersistent, however, suggesting that impacts may have diffusedoutward over time.

14. Interestingly, Goetz, Lam, and Heitlinger (1996) found thathousing developed by community-based nonprofits had positivespillover effects, while that developed by the housing authority hadnegative effects. This may be because the community-based

nonprofits they examined in Minneapolis were more sensitive tocommunity effects.


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References


Aaron, Henry J . 1972. Shelter and Subsidies: Who Benefits fromFederal Housing Policies? Washington, D.C.: BrookingsInstitution.

Bahchieva, Raisa, and Amy Hosier . 2001. Section 8 in a Tight Market,the Case of New York City. Unpublished paper, New York City Housing Authority.

Briggs, Xavier de Souza, Joe T. Darden, and Angela Aidala. 1999. In theWake of Desegregation: Early Impacts of Scattered-Site PublicHousing on Neighborhoods in Yonkers, New York. Journal ofthe American Planning Association 65, no. 1: 27-49.

Caplin, Andrew, and John Leahy . 1998. Miracle on Sixth Avenue:Information Externalities and Search. Economic Journal 108,

January: 60-74.

Cummings, Jean L., Denise DiPasquale, and Matthew E. Kahn . 2001.Inner City Homeownership Opportunities and BlackCommunity Choice. Paper presented at the Annual Meetings of the American Real Estate and Urban Economics Association,Washington, D.C., January.

Daniels, Glynis, and Michael H. Schill . 2001. State of New York CitysHousing and Neighborhoods 2001. New York University FurmanCenter for Real Estate and Urban Policy.

DeSalvo, Joseph S. 1974. Neighborhood Upgrading Effects of Middle-Income Housing Projects in New York City. Journal of UrbanEconomics 1: 269-77.

Ellen, Ingrid Gould, Michael H. Schill, Amy Ellen Schwartz, and IoanVoicu. 2001. The Role of Cities in Providing Housing Assistance:A New York Perspective. Paper presented at the New YorkUniversity Wagner School of Public Service Conference HonoringDick Netzer.

Ellen, Ingrid Gould, Michael H. Schill, Scott Susin, and Amy EllenSchwartz . 2001. Building Homes, Reviving Neighborhoods:

Spillovers from Subsidied Construction of Owner-OccupiedHousing in New York City. Journal of Housing Research 12,no. 2: 185-216.

Ellen, Ingrid Gould, and Margery Austin Turner . 1997. DoesNeighborhood Matter? Assessing Recent Evidence. HousingPolicy Debate 8, no. 4: 833-66.

Galster, George C., Anna M. Santiago, Peter Tatian, and Robin Smith .1999. Assessing Property Value Impacts of Dispersed HousingSubsidy Programs. Report to the U.S. Department of Housingand Urban Development. Washington, D.C.

Galster, George C., Peter Tatian, and Robin Smith . 1999. The Impactof Neighbors Who Use Section 8 Certificates on Property Values.Housing Policy Debate 10, no. 4: 879-917.

Goetz, Edward, Hin Kin Lam, and Anne Heitlinger . 1996. There Goesthe Neighborhood? The Impact of Subsidized Multi-Family Housing on Urban Neighborhoods. Center for Urban andRegional Affairs Working Paper no. 96-1.

Hirsch, Arnold. 1983. Making the Second Ghetto: Race andHousing in Chicago, 1940-1960

. New York: CambridgeUniversity Press.

Koch, Edward I . 1985. The State of the City: Housing Initiatives.Remarks, January 30.

Lee, Chang-Moo, Dennis P. Culhane, and Susan M. Wachter . 1999.The Differential Impacts of Federally Assisted Housing Programson Nearby Property Values: A Philadelphia Case Study. HousingPolicy Debate 10, no. 1: 75-93.

Lyons, Robert F., and Scott Loveridge. 1993. An Hedonic Estimation of

the Effect of Federally Subsidized Housing on Nearby ResidentialProperty Values. University of Minnesota, Department of Agriculture and Applied Economics Staff Paper no. P93-6.

Matulef, Mark . 1988. The Effects of Subsidized Housing on Property Values. Journal of Housing , November/December: 286-7.

McClure, Kirk. 1998. Housing Vouchers versus Housing Production:Assessing Long-Term Costs. Housing Policy Debate 9, no. 2:355-71.

Mills, Edwin S., and Bruce W. Hamilton. 1994. Urban Economics .

5th ed. New York: HarperCollins.

Newman, Sandra J., and Ann B. Schnare . 1997. . . . And a SuitableLiving Environment: The Failure of Housing Programs to Deliveron Neighborhood Quality. Housing Policy Debate 8, no. 4:703-41.


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References (Continued)


New York City Department of Housing Preservation and Development .1989. The 10 Year Plan.

. 2000. Building on a Solid Foundation: ConferenceProceedings Summary.

New York City Office of the Mayor . 1988. Press release, May 4.

Nourse, Hugh O. 1963. The Effects of Public Housing on Property Values in St. Louis. Land Economics 39: 433-41.

Olsen, Edgar O. 2001. Housing Programs for Low-IncomeHouseholds. NBER Working Paper no. 8208, April.

Ondrich, Jan, Alex Stricker, and John Yinger . 1999. Do Landlords

Discriminate? The Incidence and Causes of Racial Discriminationin Rental Housing Markets. Journal of Housing Economics 8,no. 3: 185-204.

Polinsky, Mitchell A., and Ellwood T. David. 1979. An EmpiricalReconciliation of Micro and Grouped Estimates of the Demand forHousing. Review of Economics and Statistics 61, no. 2:199-205.

Pollakowski, Henry O. 1997. The Effects of Rent Deregulationin New York City. Massachusetts Institute of Technology Centerfor Real Estate.

Rabiega, William A., Ta-Win Lin, and Linda Robinson . 1984. TheProperty Value Impacts of Public Housing Projects in Low andModerate Density Residential Neighborhoods. Land Economics60: 174-9.

Salama, Jerry J., Michael H. Schill, and Martha E. Stark . 1999.Reducing the Cost of New Housing Construction in New YorkCity. New York University Furman Center for Real Estate andUrban Policy.

Santiago, Anna M., George C. Galster, and Peter Tatian . 2001.Assessing the Property Value Impacts of the Dispersed HousingSubsidy Program in Denver. Journal of Policy Analysis andManagement 20, no. 1: 65-88.

Schafer, Robert . 1972. The Effect of BMIR Housing on Property Values. Land Economics 48: 282-6.

Schill, Michael H . 1990. Privatizing Federal Low Income HousingAssistance: The Case of Public Housing. Cornell Law Review

75: 878-948.

. 1993. Distressed Public Housing: Where Do We Go fromHere? University of Chicago Law Review 60, no. 2: 497-554.

Schill, Michael H., Ingrid Gould Ellen, Amy Ellen Schwartz, and IoanVoicu. 2001. Revitalizing Inner-City Neighborhoods: New YorkCitys Ten-Year Plan for Housing. Paper presented at the Mid-Year Meetings of the American Real Estate and Urban EconomicsAssociation, Washington, D.C.

Shroder, Mark, and Arthur Reiger . 2000. Vouchers versus Production

Revisited. Journal of Housing Research 11, no. 1: 91-107.

U.S. General Accounting Office. 2001. Federal Housing Programs:What They Cost and What They Provide. GAO-01-901R, July 18.Washington, D.C.: U.S. Government Printing Office.

The views expressed are those of the authors and do not necessarily reflect the position of the Federal Reserve Bank of New Yorkor the Federal Reserve System. The Federal Reserve Bank of New York provides no warranty, express or implied, as to theaccuracy, timeliness, completeness, merchantability, or fitness for any particular purpose of any information contained indocuments produced and provided by the Federal Reserve Bank of New York in any form or manner whatsoever.

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